How gambling cravings and self-efficacy are linked to subsequent gambling episodes

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Author(s): Hawker, Chloe O., ; Merkouris, Stephanie ; Youssef, George J. ; Dowling, Nicki A.

Journal: Addictive Behaviors

Year Published: 2021

Date Added: October 28, 2020

Up to 12% of Australians may experience some gambling harms. Reducing gambling could prevent these harms. This study looked at how a person’s gambling cravings and their confidence in resisting their cravings (i.e., self-efficacy) influence their gambling behaviour, and vice versa. Adults who gambled regularly completed short surveys twice per day for four weeks. Participants who had gambling cravings were more likely to gamble at a later time. Participants with lower craving self-efficacy spent more money gambling. If cravings were infrequent, then high gambling self-efficacy reduced gambling episodes. However, if cravings were frequent, then self-efficacy did not reduce gambling. Participants who gambled to cope spent more money gambling if they had low gambling self-efficacy. Finally, participants who gambled for positive reinforcement and those with substance use issues were more vulnerable to gambling.

Citation: Hawker, C. O., Merkouris, S.S ., Youssef, G. J., & Dowling, N. A. (2021). Exploring the associations between gambling cravings, self-efficacy, and gambling episodes: An Ecological Momentary Assessment study. Addictive Behaviors, 112, 106574. https://doi.org/10.1016/j.addbeh.2020.106574

Article DOI: https://doi.org/10.1016/j.addbeh.2020.106574

Keywords: cravings ; Ecological Momentary Assessment (EMA) ; gambling ; relapse ; self-efficacy ; smartphone

Topics: Prevention

Conceptual Framework Factors: Psychological Factors ; Resources - Harm Reduction, Prevention, and Protection ; Psychological - Judgement and Decision Making ; Gambling Resources

Response Rate: 643 people were eligible to participate from the SEIS. 365 indicated interest in participation. Of the 365, the researchers contacted at least 274 to participate and 97 completed the study. (They did not contact the remainder of the 365 participants, since they already reached their desired sample size of ~100). Response rate could be calculated as = 97/274 = 35.4%, but this may not be accurate.

Study Design: Secondary Data Analysis

Geographic Coverage: Australia, Tasmania

Study Population: Australian adults who gambled at least once per month on any gambling activity aside from the lottery (n = 97).

Sampling Procedure: Researchers recruited participants from the 4th Social and Economic Impact Study of Gambling (SEIS) in Tasmania, Australia. 5000 people completed the SEIS, and 643 were eligible to participate in this study (gambled monthly, owned a smartphone). 365 were interested in completing the 4-week study. Researchers started contacting these participants until they reached their desired sample size of 100. Three participants were later excluded, resulting in a final sample size of N=97.

Study Funding:

This study was funded by the Tasmanian Government Department of Treasury and Finance as part of the Fourth Social and Economic Impact Study. In addition, N. A. Dowling is a recipient of a Deakin University Faculty of Health Mid-Career Fellowship.